Graph related

Type of graph

PlotS presents users with a range of eight graph types to select from:

Certain graph like density, frequency and histogram require only X-axis. The variable for Y-axis for the other remaining graph has to be numeric variable. Users can interactively change the variable for the axes.

Aesthetic option

The aesthetic choice serves as a valuable function that links a variable to a visual element like color, shape, or line type (dash, dotted, solid). This enables users to add additional variables or differentiate between variables on the graph through aesthetic mapping. This functionality equips PlotS to effectively manage a wide range of data variables for analysis, setting it apart from other visualization tools.

To illustrate, we will use a hypothetical gene expression dataset (refer to Table 1) representing two rice cultivars (IR64 and N22) exposed to two types of treatments (t1 and t2), along with a control (c). Each condition has two replicates (R1, R2). Let’s create a scatter plot with aesthetic color mapped to treatment and Shape to replicate of the data. The resulting graphical representation is depicted in Figure 1.

Table 1. Expression data with two replicates of two rice cultivars under different treatment conditions.

cultivar

treatment

replicate

fpkm

IR64

t1

R1

20.90

IR64

t1

R2

17.75

IR64

t2

R1

5.90

IR64

t2

R2

3.39

IR64

c

R1

7.60

IR64

c

R2

6.60

N22

t1

R1

10.37

N22

t1

R2

11.93

N22

t2

R1

41.51

N22

t2

R2

33.64

N22

c

R1

23.81

N22

c

R2

28.01

Aesthetic setting
Aesthetic setting
Figure 1. Scatter plot with the chosen aesthetic elements - color and shape

Figure 1. Scatter plot with the chosen aesthetic elements - color and shape

Visualization of multivariate data

PlotS offers various features for multivariate analysis in addition to the features provided under Aesthetic options. Visualization of the relationship of multiple variables in a data can be done in four ways: 1. Faceting 2. Secondary Y-axis 2. Side graph 3. Inset graph

Faceting

Faceting creates tables of graphics by splitting the data into subsets and displaying the same graph for each subset. It can either be in grid or wrap. We will use the below Table2 for illustration of faceting. The data are in similar format as in Table 1, but more detail number of rows.

Faceting involves generating sets of visual representations by partitioning data into smaller groups and showcasing identical graphs for each subgroup. This can be achieved using either a wrap or grid arrangement. To exemplify the concept of faceting, we will utilize the provided Table 2. Although the data follows a format akin to Table 1, it contains a more comprehensive range of rows, providing a more detailed perspective.

Facet wrap setting
Facet wrap setting
Figure 2. displaying the wrap faceting

Figure 2. displaying the wrap faceting

Facet grid setting
Facet grid setting
Figure 2. displaying the grid faceting

Figure 2. displaying the grid faceting